This research aims to know the role and impact of participation in the capabilities of human resources programs, and for the purpose of measuring it has been determined the dimensions of these two variables by relying on standards for this purpose, was chosen as the Ministry of Higher Education and Scientific Research / device supervision and scientific calendar as one of the important departments in the ministry and includes a large number of individuals at different organizational levels for the purpose of answering a questionnaire prepared for the purpose of measurement and access to the results and the achievement of the objectives of the research and which ha

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In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error          ( λ ) in the model (SPSEM), estimated  the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo

Odontogenic cysts and tumors often form hard and soft structures that resemble odontogenesis. It is well known that amyloid is produced in Pindborg tumors; however, it is still debatable whether it is also formed in other odontogenic tumors and cysts. This study aimed to detect the presence of amyloid in different odontogenic cysts and tumors in correlation to matrix proteins secreted during enamel formation; namely amelogenin and odontogenic ameloblast‐associated protein.

Water pollution is widely regarded as one of the most pressing global challenges, exacerbated by human progress in industrial, agricultural, and technological sectors. Wastewater often contains non-biodegradable heavy metals that accumulate in living organisms. This accumulation poses significant risks to both environmental ecosystems and human health. The structures and surface morphology were characterized by FTIR, UV-vis measurements, XRD, SEM, and AFM. TiO2 nanoparticles could remove heavy metal ions (Pb2+, Cd2+, and Cr3+) from two samples (laboratory samples and real samples from Babylon battery factory in Al-Waziriya, Baghdad/Iraq) and measured by AAS. The results indicated that the removal percentages of heavy metal ions by T

       Iraq is one of the most important countries in the world that has received its share of terrorist acts by the terrorist organization the Islamic State of Iraq and al-Sham (ISIS), which has caused instability, especially during the period of ISIS's control of seven Iraqi provinces (2014-2017). This stage has caused a decline in the levels of human and economic development and its inconsistency with the capabilities and needs of the Iraqi population. Therefore, this study aims to investigate the hypothesis that there is a close relationship between the decline in development in Iraq and the brutal practices of ISIS that it committed during his period of control over many Iraqi cities and regions. This study used several method

Purpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl